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Published 20 hours ago • verified publisher icon Bioconductor

Totem

Open j0ntt opened this issue 3 years ago • 7 comments

Update the following URL to point to the GitHub repository of the package you wish to submit to Bioconductor

  • Repository: https://github.com/elolab/Totem

Confirm the following by editing each check box to '[x]'

  • [x] I understand that by submitting my package to Bioconductor, the package source and all review commentary are visible to the general public.

  • [x] I have read the Bioconductor Package Submission instructions. My package is consistent with the Bioconductor Package Guidelines.

  • [x] I understand Bioconductor Package Naming Policy and acknowledge Bioconductor may retain use of package name.

  • [x] I understand that a minimum requirement for package acceptance is to pass R CMD check and R CMD BiocCheck with no ERROR or WARNINGS. Passing these checks does not result in automatic acceptance. The package will then undergo a formal review and recommendations for acceptance regarding other Bioconductor standards will be addressed.

  • [x] My package addresses statistical or bioinformatic issues related to the analysis and comprehension of high throughput genomic data.

  • [x] I am committed to the long-term maintenance of my package. This includes monitoring the support site for issues that users may have, subscribing to the bioc-devel mailing list to stay aware of developments in the Bioconductor community, responding promptly to requests for updates from the Core team in response to changes in R or underlying software.

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  • [x] The 'devel' branch for new packages and features.
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j0ntt avatar Sep 27 '22 16:09 j0ntt

Hi @j0ntt

Thanks for submitting your package. We are taking a quick look at it and you will hear back from us soon.

The DESCRIPTION file for this package is:

Package: Totem
Type: Package
Title: A user-friendly tool for inferring tree-shaped 
  trajectories from single-cell data
Version: 0.99.0
Description: Totem is a tool designed to facilitate the inference of 
  tree-shaped trajectories from single-cell RNA-seq data. The key idea is 
  to generate 
  a large number of clustering results, rank them, and examine the resulting 
  top-ranked clustering results. The probability of finding an optimal clustering 
  increases when different clusterings are considered. Totem uses the 
  Slingshot method to smoothen the lineages of the trajectory network.
  In addition, the cell connectivity measure derived from the cluster 
  connectivity of Minimum Spanning Trees (MSTs) of the clustering results 
  can be used to aid the trajectory optimization.
Authors@R: c(person("Johannes", "Smolander",
   email = "[email protected]",
   role=c("cre", "aut")),
   person("Sini", "Junttila",
   role=c("aut")),
   person("Laura L", "Elo",
   role=c("aut")))
License: GPL-3
Imports: Matrix, plyr, dplyr, SingleCellExperiment,
        SummarizedExperiment, S4Vectors, methods, stats, utils, ape, aricode,
        cluster, cowplot, dyndimred, dynplot, dynwrap, fpc, ggplot2, princurve,
        purrr, slingshot, tibble
Depends: R(>= 4.2.0)
LazyData: FALSE
RoxygenNote: 7.2.1
Encoding: UTF-8
Suggests: knitr, rmarkdown, BiocStyle,DelayedMatrixStats
VignetteBuilder: knitr
URL: https://github.com/elolab/Totem
BugReports: https://github.com/elolab/Totem
Packaged: 2022-05-09 12:10:00 UTC; pajosm
biocViews: SingleCell, Software, Clustering, 
  RNASeq, Visualization, Transcriptomics, 
  DataRepresentation, Transcription,
  GeneExpression

bioc-issue-bot avatar Sep 27 '22 16:09 bioc-issue-bot

A reviewer has been assigned to your package. Learn what to expect during the review process.

IMPORTANT: Please read this documentation for setting up remotes to push to git.bioconductor.org. It is required to push a version bump to git.bioconductor.org to trigger a new build.

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bioc-issue-bot avatar Oct 11 '22 16:10 bioc-issue-bot

Dear Package contributor,

This is the automated single package builder at bioconductor.org.

Your package has been built on Linux, Mac, and Windows.

On one or more platforms, the build results were: "ERROR". This may mean there is a problem with the package that you need to fix. Or it may mean that there is a problem with the build system itself.

Please see the build report for more details. This link will be active for 21 days.

Remember: if you submitted your package after July 7th, 2020, when making changes to your repository push to [email protected]:packages/Totem to trigger a new build. A quick tutorial for setting up remotes and pushing to upstream can be found here.

bioc-issue-bot avatar Oct 11 '22 17:10 bioc-issue-bot

Received a valid push on git.bioconductor.org; starting a build for commit id: 1c80065808d3ac32d0dffd8f5c050d1f127597fa

bioc-issue-bot avatar Oct 27 '22 10:10 bioc-issue-bot

Dear Package contributor,

This is the automated single package builder at bioconductor.org.

Your package has been built on Linux, Mac, and Windows.

On one or more platforms, the build results were: "ERROR". This may mean there is a problem with the package that you need to fix. Or it may mean that there is a problem with the build system itself.

Please see the build report for more details. This link will be active for 21 days.

Remember: if you submitted your package after July 7th, 2020, when making changes to your repository push to [email protected]:packages/Totem to trigger a new build. A quick tutorial for setting up remotes and pushing to upstream can be found here.

bioc-issue-bot avatar Oct 27 '22 10:10 bioc-issue-bot

Received a valid push on git.bioconductor.org; starting a build for commit id: fc2d20614a1d82459ca38bb98f22bd212922aec3

bioc-issue-bot avatar Oct 27 '22 10:10 bioc-issue-bot

Dear Package contributor,

This is the automated single package builder at bioconductor.org.

Your package has been built on Linux, Mac, and Windows.

Congratulations! The package built without errors or warnings on all platforms.

Please see the build report for more details. This link will be active for 21 days.

Remember: if you submitted your package after July 7th, 2020, when making changes to your repository push to [email protected]:packages/Totem to trigger a new build. A quick tutorial for setting up remotes and pushing to upstream can be found here.

bioc-issue-bot avatar Oct 27 '22 10:10 bioc-issue-bot

Package 'Totem' Review

Thank you for submition your package to Bioconductor. The package passed check and build. However there are several things need to be fixed. Please try to answer the comments line by line when you are ready for a second review. Hope this will help you to get it done within coming release.

The DESCRIPTION file

  • [ ] R version is not clear in DESCRIPTION.

The NAMESPACE file

  • [ ] Selective imports using importFrom instead of import all with import.
    • in line 22 import(dplyr)
    • in line 23 import(dynwrap)
    • in line 24 import(purrr)
    • in line 25 import(slingshot)
    • in line 26 import(tibble)

General package development

  • Checking unit tests...
    • NOTE: Consider adding unit tests. We strongly encourage them. See https://contributions.bioconductor.org/tests.html

R code

  • [ ] NOTE: no direct slot access with @ or slot() - accessors implemented and used.
    • In file R/CoreMethods.R:
      • at line 1464 found ' slingshot_parameters <- old_trajectory@metadata$slingParams'
    • In file R/Utils.R:
      • at line 454 found ' sds@metadata$slingParams$dist.method <- slingshot.par.list$dist.method'
  • [ ] Important: vapply instead of sapply.
    • In file R/Utils.R:
      • at line 432 found ' means <- sapply(lin, function(clID){'
  • [ ] Important: warning, message, stop instead of cat and print outside of show methods.
    • In file R/CoreMethods.R:
      • at line 107 found ' cat("1. Run dimensionality reduction...")'
      • at line 114 found ' cat("2. Generate a set of clustering results...")'
      • at line 123 found ' cat("3. Select clusterings...")'
      • at line 132 found ' cat("4. Run the lineage smoothing...")'
  • [ ] NOTE: :: is not suggested in source code unless you can make sure all the packages are imported. Some people think it is better to keep ::. However please note that you need to manully double check the import items when you make any change in the DESCRIPTION file during development. My recommendation is to remove one or two repeats to force the dependency check.
    • In file R/CoreMethods.R:
      • at line 283 found ' X <- Matrix::t(logcounts(object))'
      • at line 396 found ' X <- as.matrix(Matrix::t(X))'
      • at line 631 found ' X <- as.matrix(Matrix::t(X))'
      • at line 730 found ' X <- as.matrix(Matrix::t(X))'
      • at line 826 found ' X <- as.matrix(Matrix::t(X))'
      • at line 915 found ' X <- as.matrix(Matrix::t(X))'
      • at line 939 found ' p <- cowplot::plot_grid(plotlist = plot_list)'
      • at line 1014 found ' X <- as.matrix(Matrix::t(X))'
      • at line 1021 found ' exp_matrix <- Matrix::t(logcounts(object))'
      • at line 1120 found ' X <- as.matrix(Matrix::t(X))'
      • at line 1129 found ' expression_matrix <- as.matrix(Matrix::t(logcounts(object)))'
      • at line 1319 found ' X <- as.matrix(Matrix::t(X))'
      • at line 1457 found ' X <- as.matrix(Matrix::t(X))'
    • In file R/Utils.R:
      • at line 433 found ' stats::weighted.mean(pst.full, cluster[,clID])'
      • at line 447 found ' dynwrap::wrap_data('
      • at line 450 found ' dynwrap::add_trajectory('
  • [ ] NOTE: Vectorize: for loops present, try to replace them by *apply funcitons.
    • In file R/CoreMethods.R:
      • at line 639 found ' for (kkk in names(clusterings))'
      • at line 739 found ' for (clustering_name in clustering.names)'
      • at line 925 found ' for (traj_name in traj.names) {'
      • at line 1032 found ' for (feature_name in feature.names) {'
      • at line 1041 found ' for (feature_name in feature.names) {'
    • In file R/Utils.R:
      • at line 39 found ' for (lineage in lineages)'
      • at line 45 found ' for (cluster in adjacent_clusters)'
      • at line 90 found ' for (ks_ in ks) {'
      • at line 100 found ' for (k in ks) {'
      • at line 133 found ' for (k in ks) {'
      • at line 165 found ' for (k in ks) {'
      • at line 222 found ' for (lineage in lineages)'
      • at line 271 found ' for (i in seq_len(nrow(X)))'
      • at line 499 found ' for (i in seq_along(all.cor)) {'
      • at line 505 found ' for (i in seq_along(all.cor)) {'
      • at line 510 found ' for (i in seq_len(nclust)) {'
      • at line 518 found ' for (j in seq_len(i - 1L)) {'
  • [ ] Important: Please consider to add drop=FALSE to avoid the reduction of dimension for matrices and arrays.
    • In file R/CoreMethods.R:
      • at line 199 found ' object <- object[!duplicated(rownames(object)), ]'
      • at line 211 found ' object <- object[non_expressing_genes,]'
      • at line 289 found ' X <- X[,dim.red.features]'
      • at line 529 found ' all.clust.scores <- all.clust.scores[ks,]'
    • In file R/Utils.R:
      • at line 43 found ' last_cl_cons <- mst.out[last_cluster,]'
      • at line 244 found ' milestone_network <- milestone_network[!duplicated(milestone_pairs),]'
  • [ ] NOTE: Functional programming: code repetition.
    • repetition in ChangeTrajRoot.SingleCellExperiment , ReturnMSTNetwork.SingleCellExperiment , RunClustering.SingleCellExperiment, RunSmoothing.SingleCellExperiment , VizCellConnectivity.SingleCellExperiment, VizClustering.SingleCellExperiment, VizFeatureExpression.SingleCellExperiment , VizMST.SingleCellExperiment and VizSmoothedTraj.SingleCellExperiment
      • in ChangeTrajRoot.SingleCellExperiment
        • line 4: if (identical(reducedDimNames(object), character(0))) {
        • line 5: message("No dimensionality reduced data available. ",
        • line 6: "Using data in the 'logcounts' slot.")
        • line 7: X <- logcounts(object)
        • line 8: X <- as.matrix(Matrix::t(X))
        • line 9: }
        • line 10: else {
        • line 11: X <- reducedDim(object)
      • in ReturnMSTNetwork.SingleCellExperiment
        • line 2: {
        • line 3: if (identical(reducedDimNames(object), character(0))) {
        • line 4: message("No dimensionality reduced data available. ",
        • line 5: "Using data in the 'logcounts' slot.")
        • line 6: X <- logcounts(object)
        • line 7: X <- as.matrix(Matrix::t(X))
        • line 8: }
        • line 9: else {
        • line 10: X <- reducedDim(object)
      • in RunClustering.SingleCellExperiment
        • line 3: {
        • line 4: if (identical(reducedDimNames(object), character(0))) {
        • line 5: message("No dimensionally reduced data available.",
        • line 6: " Using data in the 'logcounts' slot.")
        • line 7: X <- logcounts(object)
        • line 8: X <- as.matrix(Matrix::t(X))
        • line 9: }
        • line 10: else {
        • line 11: X <- reducedDim(object)
      • in RunSmoothing.SingleCellExperiment
        • line 1: function (object, slingshot.par.list)
        • line 2: {
        • line 3: clusterings <- metadata(object)$totem$selected.clustering
        • line 4: if (identical(reducedDimNames(object), character(0))) {
        • line 5: message("No dimensionality reduced data available. ",
        • line 6: "Using data in the 'logcounts' slot.")
        • line 7: X <- logcounts(object)
        • line 8: X <- as.matrix(Matrix::t(X))
        • line 9: }
        • line 10: else {
        • line 11: X <- reducedDim(object)
        • line 12: }
      • in VizCellConnectivity.SingleCellExperiment
        • line 2: {
        • line 3: if (identical(reducedDimNames(object), character(0))) {
        • line 4: message("No dimensionality reduced data available. ",
        • line 5: "Using data in the 'logcounts' slot.")
        • line 6: X <- logcounts(object)
        • line 7: X <- as.matrix(Matrix::t(X))
        • line 8: }
        • line 9: else {
        • line 10: X <- reducedDim(object)
        • line 11: }
      • in VizClustering.SingleCellExperiment
        • line 3: {
        • line 4: if (identical(reducedDimNames(object), character(0))) {
        • line 5: message("No dimensionality reduced data available. ",
        • line 6: "Using data in the 'logcounts' slot.")
        • line 7: X <- logcounts(object)
        • line 8: X <- as.matrix(Matrix::t(X))
        • line 9: }
        • line 10: else {
        • line 11: X <- reducedDim(object)
        • line 12: }
      • in VizFeatureExpression.SingleCellExperiment
        • line 3: {
        • line 4: if (identical(reducedDimNames(object), character(0))) {
        • line 5: message("No dimensionality reduced data available. ",
        • line 6: "Using data in the 'logcounts' slot.")
        • line 7: X <- logcounts(object)
        • line 8: X <- as.matrix(Matrix::t(X))
        • line 9: }
        • line 10: else {
        • line 11: X <- reducedDim(object)
        • line 12: }
      • in VizMST.SingleCellExperiment
        • line 2: {
        • line 3: if (identical(reducedDimNames(object), character(0))) {
        • line 4: message("No dimensionality reduced data available. ",
        • line 5: "Using data in the 'logcounts' slot.")
        • line 6: X <- logcounts(object)
        • line 7: X <- as.matrix(Matrix::t(X))
        • line 8: }
        • line 9: else {
        • line 10: X <- reducedDim(object)
        • line 11: }
      • in VizSmoothedTraj.SingleCellExperiment
        • line 3: {
        • line 4: if (identical(reducedDimNames(object), character(0))) {
        • line 5: message("No dimensionality reduced data available. ",
        • line 6: "Using data in the 'logcounts' slot.")
        • line 7: X <- logcounts(object)
        • line 8: X <- as.matrix(Matrix::t(X))
        • line 9: }
        • line 10: else {
        • line 11: X <- reducedDim(object)
        • line 12: }
    • repetition in GenerateMST , ReturnMSTNetwork.SingleCellExperiment and VizOneMST
      • in GenerateMST
        • line 7: centroids <- ClusterCentroids(clustering, X)
        • line 8: mst_out <- mst(SlingshotDistanceMatrix(x = X, centers = centroids,
        • line 9: clusters = clustering))
        • line 10: msts[[k]] <- mst_out
      • in ReturnMSTNetwork.SingleCellExperiment
        • line 14: centroids <- ClusterCentroids(clustering, X)
        • line 15: mst_out <- mst(SlingshotDistanceMatrix(x = X, centers = centroids,
        • line 16: clusters = clustering))
        • line 17: return(mst_out)
      • in VizOneMST
        • line 2:{
        • line 3: centroids <- ClusterCentroids(clustering, X)
        • line 4: mst_out <- mst(SlingshotDistanceMatrix(x = X, centers = centroids,
        • line 5: clusters = clustering))

Documentation

  • [ ] Note: Vignette includes motivation for submitting to Bioconductor as part of the abstract/intro of the main vignette.
    • rmd file vignettes/Totem.Rmd

jianhong avatar Oct 28 '22 15:10 jianhong

Hi, can you explain what is the difference between comments that are labeled as notes and those that are important? Since the new Bioconductor version is available, I suppose I need to make changes to my package so that it supports the new Bioconductor version?

j0ntt avatar Nov 10 '22 10:11 j0ntt

Important: must be discussed or resolved Note: need to be improved but not required Best!Your sincerely,Jianhong OuOn Nov 10, 2022, at 5:31 AM, Johannes Smolander @.***> wrote: Hi, can you explain what is the difference between comments that are labeled as notes and those that are important? Since the new Bioconductor version is available, I suppose I need to make changes to my package so that it supports the new Bioconductor version?

—Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you were assigned.Message ID: @.***>

jianhong avatar Nov 10 '22 11:11 jianhong

@j0ntt may we expect updates to your package soon?

lshep avatar Dec 16 '22 12:12 lshep

This issue is being closed because there has been no progress for an extended period of time. You may reopen the issue when you have the time to actively participate in the review / submission process. Please also keep in mind that a package accepted to Bioconductor requires a commitment on your part to ongoing maintenance.

Thank you for your interest in Bioconductor.

bioc-issue-bot avatar Feb 17 '23 14:02 bioc-issue-bot